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Refine Allocator Config error message friendly (#165288)

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* __->__ #165288
Pull Request resolved: https://github.com/pytorch/pytorch/pull/165288
Approved by: https://github.com/albanD
This commit is contained in:
Yu, Guangye
2025-10-17 17:16:41 +00:00
committed by PyTorch MergeBot
parent 5d62b63a76
commit 4888ed440e
4 changed files with 23 additions and 22 deletions
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16
c10/core/AllocatorConfig.cpp
View File

@ -46,7 +46,7 @@ size_t AcceleratorAllocatorConfig::roundup_power2_divisions(size_t size) {
63 - llvm::countLeadingZeros(kRoundUpPowerOfTwoStart);
const size_t interval_end =
63 - llvm::countLeadingZeros(kRoundUpPowerOfTwoEnd);
TORCH_CHECK(
TORCH_CHECK_VALUE(
interval_end - interval_start == kRoundUpPowerOfTwoIntervals,
"kRoundUpPowerOfTwoIntervals mismatch");
@ -65,7 +65,7 @@ size_t AcceleratorAllocatorConfig::parseMaxSplitSize(
std::numeric_limits<size_t>::max() / kMB;
size_t val_env = tokenizer.toSizeT(++i);
TORCH_CHECK(
TORCH_CHECK_VALUE(
val_env >= min_allowed_split_size_mb,
"CachingAllocator option max_split_size_mb too small, must be >= ",
min_allowed_split_size_mb);
@ -84,7 +84,7 @@ size_t AcceleratorAllocatorConfig::parseMaxNonSplitRoundingSize(
std::numeric_limits<size_t>::max() / kMB;
size_t val_env = tokenizer.toSizeT(++i);
TORCH_CHECK(
TORCH_CHECK_VALUE(
val_env >= min_allowed_split_size_mb,
"CachingAllocator option max_non_split_rounding_mb too small, must be >= ",
min_allowed_split_size_mb);
@ -99,7 +99,7 @@ size_t AcceleratorAllocatorConfig::parseGarbageCollectionThreshold(
size_t i) {
tokenizer.checkToken(++i, ":");
double val_env = tokenizer.toDouble(++i);
TORCH_CHECK(
TORCH_CHECK_VALUE(
val_env > 0 && val_env < 1.0,
"garbage_collect_threshold is invalid, set it in (0.0, 1.0)");
garbage_collection_threshold_ = val_env;
@ -120,7 +120,7 @@ size_t AcceleratorAllocatorConfig::parseRoundUpPower2Divisions(
size_t value_index = i;
tokenizer.checkToken(++i, ":");
size_t value = tokenizer.toSizeT(++i);
TORCH_CHECK(
TORCH_CHECK_VALUE(
value == 0 || llvm::isPowerOf2_64(value),
"For roundups, the divisions has to be power of 2 or 0 to disable roundup ");
@ -133,7 +133,7 @@ size_t AcceleratorAllocatorConfig::parseRoundUpPower2Divisions(
value);
} else {
size_t boundary = tokenizer.toSizeT(value_index);
TORCH_CHECK(
TORCH_CHECK_VALUE(
llvm::isPowerOf2_64(boundary),
"For roundups, the intervals have to be power of 2 ");
@ -163,7 +163,7 @@ size_t AcceleratorAllocatorConfig::parseRoundUpPower2Divisions(
"Expected closing bracket ']' in ConfigTokenizer but reached end of config");
} else { // Keep this for backwards compatibility
size_t value = tokenizer.toSizeT(i);
TORCH_CHECK(
TORCH_CHECK_VALUE(
llvm::isPowerOf2_64(value),
"For roundups, the divisions has to be power of 2 ");
std::fill(
@ -223,7 +223,7 @@ void AcceleratorAllocatorConfig::parseArgs(const std::string& env) {
// If a device-specific configuration parser hook is registered, it will
// check if the key is unrecognized.
if (device_config_parser_hook_) {
TORCH_CHECK(
TORCH_CHECK_VALUE(
getKeys().find(key) != getKeys().end(),
"Unrecognized key '",
key,

4
c10/core/AllocatorConfig.h
View File

@ -76,7 +76,7 @@ class ConfigTokenizer {
} else if (token == "False") {
return false;
} else {
TORCH_CHECK(
TORCH_CHECK_VALUE(
false,
"Expected 'True' or 'False' at index ",
i,
@ -253,7 +253,7 @@ class C10_API AcceleratorAllocatorConfig {
device_config_parser_hook_ = std::move(hook);
auto& mutable_keys = getMutableKeys();
for (auto& key : keys) {
TORCH_CHECK(
TORCH_CHECK_VALUE(
mutable_keys.insert(key).second,
"Duplicated key '",
key,

13
c10/cuda/CUDAAllocatorConfig.cpp
View File

@ -20,7 +20,7 @@ size_t CUDAAllocatorConfig::parseAllocatorConfig(
tokenizer.checkToken(++i, ":");
i++; // Move to the value after the colon
#ifdef USE_ROCM
TORCH_CHECK(
TORCH_CHECK_VALUE(
((tokenizer[i] == "native") || (tokenizer[i] == PYTORCH_TOKEN1) ||
(tokenizer[i] == PYTORCH_TOKEN2)),
"Unknown allocator backend, "
@ -36,7 +36,7 @@ size_t CUDAAllocatorConfig::parseAllocatorConfig(
" != ",
get()->name());
#else // USE_ROCM
TORCH_CHECK(
TORCH_CHECK_VALUE(
((tokenizer[i] == "native") || (tokenizer[i] == PYTORCH_TOKEN1)),
"Unknown allocator backend, "
"options are native and " PYTORCH_TOKEN1);
@ -109,7 +109,7 @@ void CUDAAllocatorConfig::parseArgs(const std::string& env) {
} else {
const auto& keys =
c10::CachingAllocator::AcceleratorAllocatorConfig::getKeys();
TORCH_CHECK(
TORCH_CHECK_VALUE(
keys.find(key) != keys.end(),
"Unrecognized key '",
key,
@ -151,12 +151,12 @@ size_t CUDAAllocatorConfig::parsePinnedNumRegisterThreads(
size_t i) {
tokenizer.checkToken(++i, ":");
size_t val2 = tokenizer.toSizeT(++i);
TORCH_CHECK(
TORCH_CHECK_VALUE(
llvm::isPowerOf2_64(val2),
"Number of register threads has to be power of 2, got ",
val2);
auto maxThreads = CUDAAllocatorConfig::pinned_max_register_threads();
TORCH_CHECK(
TORCH_CHECK_VALUE(
val2 <= maxThreads,
"Number of register threads should be less than or equal to ",
maxThreads,
@ -171,7 +171,8 @@ size_t CUDAAllocatorConfig::parsePinnedReserveSegmentSize(
size_t i) {
tokenizer.checkToken(++i, ":");
size_t val2 = tokenizer.toSizeT(++i);
TORCH_CHECK(val2 > 0, "Pinned reserve segment size has to be greater than 0");
TORCH_CHECK_VALUE(
val2 > 0, "Pinned reserve segment size has to be greater than 0");
m_pinned_reserve_segment_size_mb = val2;
return i;
}

12
test/test_cuda.py
View File

@ -4582,21 +4582,21 @@ class TestCudaMallocAsync(TestCase):
reg_mem = torch.cuda.memory_stats()[key_allocated]
self.assertEqual(reg_mem - start_mem, nbytes)
with self.assertRaises(RuntimeError):
with self.assertRaises(ValueError):
torch.cuda.memory._set_allocator_settings("foo:1,bar:2")
with self.assertRaises(RuntimeError):
with self.assertRaises(ValueError):
torch.cuda.memory._set_allocator_settings(
"garbage_collection_threshold:1.2"
)
with self.assertRaises(RuntimeError):
with self.assertRaises(ValueError):
torch.cuda.memory._set_allocator_settings("max_split_size_mb:2")
with self.assertRaises(RuntimeError):
with self.assertRaises(ValueError):
torch.cuda.memory._set_allocator_settings("release_lock_on_cudamalloc:none")
with self.assertRaises(RuntimeError):
with self.assertRaises(ValueError):
torch.cuda.memory._set_allocator_settings(
"pinned_use_cuda_host_register:none"
)
@ -4606,7 +4606,7 @@ class TestCudaMallocAsync(TestCase):
"pinned_num_register_threads:none"
)
with self.assertRaises(RuntimeError):
with self.assertRaises(ValueError):
torch.cuda.memory._set_allocator_settings(
"pinned_num_register_threads:1024"
)